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Modeling, simulation, and prediction of global energy indices: a differential approach

Stephen Ndubuisi NNAMCHI, Onyinyechi Adanma NNAMCHI, Janice Desire BUSINGYE, Maxwell Azubuike IJOMAH, Philip Ikechi OBASI

Frontiers in Energy 2022, Volume 16, Issue 2,   Pages 375-392 doi: 10.1007/s11708-021-0723-6

Abstract: Modeling, simulation, and prediction of global energy indices remain veritable tools for econometric,engineering, analysis, and prediction of energy indices.The exact solutions are ideal for interpolative prediction of historic data.an innovative model, which is the synergy of deflated and inflated prediction factors.The innovative model yielded a trendy prediction data for energy consumption, gross domestic product,

Keywords： energy indices     differential model     normalization     simulation     inflation/deflation     predictive factor andprediction rate    

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Trend detection and stochastic simulation prediction of streamflow at Yingluoxia hydrological station

Chenglong ZHANG,Mo LI,Ping GUO

Frontiers of Agricultural Science and Engineering 2017, Volume 4, Issue 1,   Pages 81-96 doi: 10.15302/J-FASE-2016112

Abstract: Investigating long-term variation and prediction of streamflow are critical to regional water resourceNext, the Monte Carlo stochastic simulation technique was used to simulate these stochastic components

Keywords： Monte Carlo     nonstationary     trend detection     streamflow prediction     decomposition and ensemble     Yingluoxia    

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The prediction technology study of fatigue life for key parts of a tracked vehicle’s suspension system

WANG Hongyan, RUI Qiang, HE Xiaojun

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 1,   Pages 68-71 doi: 10.1007/s11465-007-0011-0

Abstract: of the tracked vehicle suspension system including a flexible torsion bar was built based on dynamic simulationNode force and stress results of the torsion bar from last step simulation were acquired; taking into

Keywords： dynamic simulation     simulation software     allusion     influential     material    

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Combustion mechanism development and CFD simulation for the prediction of soot emission during flaring

Anan Wang,Helen H. Lou,Daniel Chen,Anfeng Yu,Wenyi Dang,Xianchang Li,Christopher Martin,Vijaya Damodara,Ajit Patki

Frontiers of Chemical Science and Engineering 2016, Volume 10, Issue 4,   Pages 459-471 doi: 10.1007/s11705-016-1594-y

Abstract: It was observed that simulation results agree well with experimental data.

Keywords： flare     soot emission     combustion mechanism     CFD simulation    

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Study on Reliability Prediction and Simulation for Mechanical System Undergoing Maintenance

Huang Liangpei,Yin Xiyun and Yue Wenhui

Strategic Study of CAE 2007, Volume 9, Issue 12,   Pages 69-74

Abstract: By means of simulation of the system reliability model, concerned parameters with mechanical systems

Keywords： reassembly and maintenance     reliability prediction     age distribution     failure rate    

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 61-79 doi: 10.1007/s11709-020-0684-6

Abstract: Concrete compressive strength prediction is an essential process for material design and sustainabilityANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96

Keywords： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive    

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Finite element prediction on the response of non-uniformly arranged pile groups considering progressive

Qian-Qing ZHANG, Shan-Wei LIU, Ruo-Feng FENG, Jian-Gu QIAN, Chun-Yu CUI

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 961-982 doi: 10.1007/s11709-020-0632-5

Abstract: A uniform arrangement of individual piles is commonly adopted in the conventional pile group foundation, and basin-shaped settlement is often observed in practice. Large differential settlement of pile groups will decrease the use-safety requirements of building, even cause the whole-building tilt or collapse. To reduce differential settlement among individual piles, non-uniformly arranged pile groups can be adopted. This paper presents a finite element analysis on the response of pile groups with different layouts of individual piles in pile groups. Using the user-defined subroutine FRIC as the secondary development platform, a softening model of skin friction and a hyperbolic model of end resistance are introduced into the contact pair calculation of ABAQUS software. As to the response analysis of a single pile, the reliability of the proposed secondary development method of ABAQUS software is verified using an iterative computer program. The reinforcing effects of individual piles is then analyzed using the present finite element analysis. Furthermore, the response of non-uniformly arranged pile groups, e.g., individual piles with variable length and individual piles with variable diameter, is analyzed using the proposed numerical analysis method. Some suggestions on the layout of individual piles are proposed to reduce differential settlement and make full use of the bearing capacity of individual piles in pile groups for practical purposes.

Keywords： numerical simulation     non-uniformly arranged pile groups     differential settlement     pile-soil interaction    

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Spatial prediction of soil contamination based on machine learning: a review

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1

Abstract:

● A review of machine learning (ML) for spatial prediction of soil

Keywords： Soil contamination     Machine learning     Prediction     Spatial distribution    

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Meteorological technology application and development in wind energy resources utilization

Song Lili,Zhou Rongwei,Yang Zhenbin,Zhu Rong,

Strategic Study of CAE 2012, Volume 14, Issue 9,   Pages 96-101

Abstract: technical issues and direction should be noted in the applying process of wind energy assessment, numerical simulationand numerical prediction technology.

Keywords： wind power resource     meteorological technology     observation and assessment     simulation and prediction    

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 496-506 doi: 10.1007/s11684-021-0828-7

Abstract: The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients’ physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.

Keywords： XGBoost     deep neural network     healthcare     risk prediction    

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Position-varying surface roughness prediction method considering compensated acceleration in milling

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 855-867 doi: 10.1007/s11465-021-0649-z

Abstract: Aiming at surface roughness prediction in the machining process, this paper proposes a position-varyingsurface roughness prediction method based on compensated acceleration by using regression analysis.i>R-square proving the effectiveness of the filtering features, is selected as the input of the predictionMoreover, the prediction curve matches and agrees well with the actual surface state, which verifies

Keywords： surface roughness prediction     compensated acceleration     milling     thin-walled workpiece    

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Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Frontiers of Structural and Civil Engineering doi: 10.1007/s11709-023-0961-2

Abstract: Deep excavations in dense urban areas have caused damage to nearby existing structures in numerous past construction cases. Proper assessment is crucial in the initial design stages. This study develops equations to predict the existing pile bending moment and deflection produced by adjacent braced excavations. Influential parameters (i.e., the excavation geometry, diaphragm wall thickness, pile geometry, strength and small-strain stiffness of the soil, and soft clay thickness) were considered and employed in the developed equations. It is practically unfeasible to obtain measurement data; hence, artificial data for the bending moment and deflection of existing piles were produced from well-calibrated numerical analyses of hypothetical cases, using the three-dimensional finite element method. The developed equations were established through a multiple linear regression analysis of the artificial data, using the transformation technique. In addition, the three-dimensional nature of the excavation work was characterized by considering the excavation corner effect, using the plane strain ratio parameter. The estimation results of the developed equations can provide satisfactory pile bending moment and deflection data and are more accurate than those found in previous studies.

Keywords： pile responses     excavation     prediction     deflection     bending moments    

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Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

Frontiers in Energy 2016, Volume 10, Issue 4,   Pages 479-488 doi: 10.1007/s11708-016-0425-7

Abstract: In this paper a novel method for reliability prediction and validation of nuclear power units in serviceThe accuracy of the reliability prediction can be evaluated according to the comparison between the predictedFurthermore, the reliability prediction method is validated using the nuclear power units in North American

Keywords： nuclear power units in service     reliability     reliability prediction     equivalent availability factors    

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Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 171-175 doi: 10.1007/s11465-009-0091-0

Abstract: Trend prediction technology is the key technology to achieve condition-based maintenance of mechanicalTo ensure the normal operation of units and save maintenance costs, trend prediction technology is studiedThe main methods of the technology are given, the trend prediction method based on neural network isThe industrial site verification shows that the proposed trend prediction technology can reflect the

Keywords： water injection units     condition-based maintenance     trend prediction    

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Title Author Date Type Operation

Modeling, simulation, and prediction of global energy indices: a differential approach

Stephen Ndubuisi NNAMCHI, Onyinyechi Adanma NNAMCHI, Janice Desire BUSINGYE, Maxwell Azubuike IJOMAH, Philip Ikechi OBASI

Journal Article

Trend detection and stochastic simulation prediction of streamflow at Yingluoxia hydrological station

Chenglong ZHANG,Mo LI,Ping GUO

Journal Article

The prediction technology study of fatigue life for key parts of a tracked vehicle’s suspension system

WANG Hongyan, RUI Qiang, HE Xiaojun

Journal Article

Combustion mechanism development and CFD simulation for the prediction of soot emission during flaring

Anan Wang,Helen H. Lou,Daniel Chen,Anfeng Yu,Wenyi Dang,Xianchang Li,Christopher Martin,Vijaya Damodara,Ajit Patki

Journal Article

Study on Reliability Prediction and Simulation for Mechanical System Undergoing Maintenance

Huang Liangpei,Yin Xiyun and Yue Wenhui

Journal Article

Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Journal Article

Finite element prediction on the response of non-uniformly arranged pile groups considering progressive

Qian-Qing ZHANG, Shan-Wei LIU, Ruo-Feng FENG, Jian-Gu QIAN, Chun-Yu CUI

Journal Article

Spatial prediction of soil contamination based on machine learning: a review

Journal Article

Meteorological technology application and development in wind energy resources utilization

Song Lili,Zhou Rongwei,Yang Zhenbin,Zhu Rong,

Journal Article

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Journal Article

Position-varying surface roughness prediction method considering compensated acceleration in milling

Journal Article

Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Journal Article

Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

Journal Article

The extension of simulation —— from system simulation to domain simulation

28 Nov 2020

Conference Videos

Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

Journal Article